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Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low‐level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low‐level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low‐level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter‐comparability of studies. Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low-level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low-level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low-level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter-comparability of studies.

Nocturnal avian migration flyways remain an elusive concept, as we have largely lacked methods to map their full extent. We used the network of European weather radars to investigate nocturnal bird movements at the scale of the European flyway. We mapped the main migration directions and showed the intensity of movement across part of Europe by extracting biological information from 70 weather radar stations from northern Scandinavia to Portugal, during the autumn migration season of 2016. On average, over the 20 nights and all sites, 389 birds passed per 1 km transect per hour. The night with highest migration intensity showed an average of 1621 birds km–1 h–1 passing the radar stations, but there was considerable geographical and temporal variation in migration intensity. The highest intensity of migration was seen in central France. The overall migration directions showed strong southwest components. Migration dynamics were strongly related to synoptic wind conditions. A wind‐related mass migration event occurred immediately after a change in wind conditions, but quickly diminished even when supporting winds continued to prevail. This first continental‐scale study using the European network of weather radars demonstrates the wealth of information available and its potential for investigating large‐scale bird movements, with consequences for ecosystem function, nutrient transfer, human and livestock health, and civil and military aviation.

The texture, composition, and morphology of dunes observed in the equatorial regions of Titan may reflect present and/or past climatic conditions. Determining the physio-chemical properties and the morphodynamics of Titan's dunes is therefore essential to understanding of the climatic and geological history of the largest moon of Saturn. We quantitatively derived average surface properties of dune and interdune areas (texture, composition) from modeling of the microwave backscattered signal and Monte-Carlo inversion of the despeckled Cassini/SAR data over Titan's three largest sand seas: Belet, Shangri-La and Fensal. We present the first analysis of the backscatter functions extracted from despeckled SAR images that cover such a large range in incidence angles, including data from the beginning of the Cassini mission up to its Grand Finale. We show that dunes and interdunes have significantly different physical properties. Dunes are found to be more microwave absorbent than interdunes. Additionally, potential secondary bedforms, such as ripples and avalanches, may have been detected, providing potential evidence for currently active dunes and sediment transport. Our modelling shows that the interdunes have multi-scale roughnesses with higher dielectric constants than the dunes which have a low dielectric constant consistent with organic sand. The radar brightness of the interdunes can be explained by the presence of a shallow layer of significantly larger organic grains, possibly non-mobilized by the winds. {Together, our} findings suggest that Titan's sand seas evolve under the current multi-directional wind regimes with dunes that elongate with their crests aligned in the residual drift direction., Accepted to JGR-E on Oct 2nd 2019

Temporal variations in ice sheet flow directly impact the internal structure within ice sheets through englacial deformation. Large-scale changes in the vertical stratigraphy within ice sheets have been previously conducted on centennial to millennial timescales; however, intra-annual changes in the morphology of internal layers have yet to be explored. Over a period of two years, we use autonomous phase-sensitive radio-echo sounding (ApRES) to track the daily displacement of internal layers on Store Glacier, West Greenland to millimeter accuracy. At a site located ~30 km from the calving terminus, where the ice is ~600m thick and flows at ~700m/yr, we measure distinct seasonal variations in vertical velocities and vertical strain rates over a two-year period. Prior to the melt season (March–June), we observe increasingly non-linear englacial deformation with negative vertical strain rates (i.e. strain thinning) in the upper half of the ice column of ~0.03 a-1, whereas the ice below thickens under vertical strain reaching up to 0.16 a-1. Early in the melt season (June–July), vertical thinning gradually ceases as the glacier increasingly thickens. During late summer to midwinter (August–February), vertical thickening occurs linearly throughout the entire ice column, with strain rates averaging 0.016 a-1. We show that these complex variations are unrelated to topographic setting and localized basal slip, and hypothesize that this seasonality is driven by far-field perturbations in the glacier’s force balance, in this case generated by variations in basal hydrology near the glacier’s terminus and propagated tens of kilometers upstream through longitudinal coupling.

The Galileo E6 band operates at a nonprimary frequency band within the L-band. This presents challenging situations in the vicinity of other, legitimate, radiolocation services. This is the case for Air Traffic Control (ATC) radar, which is seen as an in-band–pulsed interference by a GNSS receiver. This paper provides a detailed study of the impact of such interference, as well as localization approaches. Particularly, the paper describes the ATC jamming event captured on a GNSS permanent station, its effects on a real receiver, and how it was tracked to localize the source of interference. An ultra low-cost array-based solution is prototyped, based on commercial off-the-shelf devices, that implements a two-element array. Experimental results are shown and discussed using real data, validating the localization performance of the prototype. © 2019 Institute of Navigation

A total of 118 stratiform water clouds were observed by ground-based remote sensing instruments at the Mace Head Atmospheric Research Station on the west coast of Ireland from 2009 to 2015. Microphysical and optical characteristics of these clouds were studied as well as the impact of aerosols on these properties. Microphysical and optical cloud properties were derived using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds). Ground-based in situ measurements of aerosol concentrations and the transport path of air masses at cloud level were investigated as well. The cloud properties were studied in dependence of the prevailing air mass at cloud level and season. We found higher cloud droplet number concentrations (CDNC) and smaller effective radii (r(eff)) with greater pollution. Median CDNC ranged from 60 cm(-3) in marine air masses to 160 cm(-3) in continental air. Median reff ranged from 8 mu m in polluted conditions to 10 mu m in marine air. Effective droplet size distributions were broader in marine than in continental cases. Cloud optical thickness (COT) and albedo were lower in cleaner air masses and higher in more polluted conditions, with medians ranging from 2.1 to 4.9 and 0.22 to 0.39, respectively. However, calculation of COT and albedo was strongly affected by liquid water path (LWP) and departure from adiabatic conditions. A comparison of SYRSOC results with MODIS (Moderate-Resolution Imaging Spectroradiometer) observations showed large differences for LWP and COT but good agreement for reff with a linear fit with slope near 1 and offset of -1 mu m.

This paper illustrates how multiple scattering signatures affect Global Precipitation Measuring (GPM) Mission Dual‐Frequency Precipitation Radar (DPR) Ku and Ka band reflectivity measurements and how they are consistent with prelaunch assessments based on theoretical considerations and confirmed by airborne observations. In particular, in the presence of deep convection, certain characteristics of the dual‐wavelength reflectivity profiles cannot be explained with single scattering, whereas they are readily explained by multiple‐scattering theory. Examples of such signatures are the absence of surface reflectivity peaks and anomalously small reflectivity slopes in the lower troposphere. These findings are relevant for DPR‐based rainfall retrievals and stratiform/convective classification algorithms when dealing with deep convective regions. A path to refining the rainfall inversion problem is proposed by adopting a methodology based on a forward operator which accounts for multiple scattering. A retrieval algorithm based on this methodology is applied to a case study over Africa, and it is compared to the standard DPR products obtained with the at‐launch version of the standard algorithms., Key Points GPM‐DPR observations are affected by multiple scattering in deep convectionThe multiple‐scattering tail can be used for better characterizing the ice phaseMultiple‐scattering effects can be included in DPR retrievals

While basically RADARs and LIDARs share the same principles of measurements, because of their different wavelengths, RADARs and LIDARs are sensitive to different characteristics of the atmosphere. LIDARs are used primarily for clear air sensing of molecular and particulate species (including ice clouds). RADAR measurements are most widely used for cloud and rain sensing. However, there are overlaps in the capabilities and new applications take advantage of recently developed installations of RADAR and LIDAR on the same aircraft. Several books exist which detail LIDAR or RADAR techniques and applications. It is not the objective of this chapter to fully describe such techniques or to delve into details about electromagnetic interaction processes. Rather, the objectives of this chapter are to (i)present, in parallel, optical and microwave measurement principles focusing on similarities and differences; (ii) highlight recent advances in observations, including synergetic ones; and (iii) to present state-of-the-art results related to the characterization of the atmospheric parameters and composition from airborne LIDAR and RADAR observations. Surface and subsurface characterization are not part of this review.